JoXSZ：星系团的联合X-SZ拟合代码
JoXSZ: Joint X-SZ fitting code for galaxy clusters
摘要：
热Sunyaev-Zeldovich（SZ）效应和X射线发射提供了独立的和高度互补的探测团内介质的热力学。我们提出JoXSZ，第一个公开可用的代码，旨在共同适应SZ和X射线数据来自各种仪器，以获得热力学配置文件的星系团。JoXSZ遵循完全贝叶斯正演模拟方法，考虑SZ校准不确定性和X射线背景水平系统。它改进了大多数最先进的，但不是公开可用的分析，因为它采用了正确的联合似然泊松-高斯表达式，充分利用了观测中包含的信息，即使在数据集内缺失值的情况下，也具有更包容的误差预算，并在代码的各个部分采用一致的温度，当用户需要时，允许X射线和SZ气体质量加权温度之间的差异。JoXSZ解释了光束拖尾和数据分析传递函数，解释了SZ和X射线转换因子的温度和金属度依赖性，采用了热力学曲线的灵活参数化，并根据用户要求允许采用或放松流体静力学平衡（HE）的假设。当HE成立时，JoXSZ对封闭质量的径向导数使用物理（正）先验，并导出质量分布和过密度半径$r_Δ$。由于这些原因，JoXSZ超越了简单的SZ和电子密度拟合。我们说明了使用JoXSZ结合钱德拉和NIKA的高红移集群CL J1226.9+3332的数据。代码是用Python编写的，它是完整的文档，用户可以根据自己的需求和要求自由定制他们的分析。JoXSZ在GitHub上公开。
英文摘要：
The thermal Sunyaev-Zeldovich (SZ) effect and the X-ray emission offer separate and highly complementary probes of the thermodynamics of the intracluster medium. We present JoXSZ, the first publicly available code designed to jointly fit SZ and X-ray data coming from various instruments to derive the thermodynamic profiles of galaxy clusters. JoXSZ follows a fully Bayesian forward-modelling approach, accounts for the SZ calibration uncertainty and X-ray background level systematic. It improves upon most state-of-the-art, and not publicly available, analyses because it adopts the correct Poisson-Gauss expression for the joint likelihood, makes full use of the information contained in the observations, even in the case of missing values within the datasets, has a more inclusive error budget, and adopts a consistent temperature across the various parts of the code, allowing for differences between X-ray and SZ gas mass weighted temperatures when required by the user. JoXSZ accounts for beam smearing and data analysis transfer function, accounts for the temperature and metallicity dependencies of the SZ and X-ray conversion factors, adopts flexible parametrization for the thermodynamic profiles, and on user request allows either adopting or relaxing the assumption of hydrostatic equilibrium (HE). When HE holds, JoXSZ uses a physical (positive) prior on the radial derivative of the enclosed mass and derives the mass profile and overdensity radii $r_Δ$. For these reasons, JoXSZ goes beyond simple SZ and electron density fits. We illustrate the use of JoXSZ by combining Chandra and NIKA data on the high-redshift cluster CL J1226.9+3332. The code is written in Python, it is fully documented and the users are free to customize their analysis in accordance with their needs and requirements. JoXSZ is publicly available on GitHub.
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